In a conventional facsimile or television-telephone set, transmission data is compressed and encoded so that the data transmission amount is decreased. As a method for compressing image data, an estimate encoding method and a transformation encoding method are utilized conventionally. In the estimate encoding method, a signal to be next supplied is estimated in accordance with a signal which has been known by decoding an encoded signal, so that only a signal component which is different in the estimation from a correct signal is transmitted to decrease the amount of information to be encoded.
In the transformation encoding method, only coefficients of components, signal electric power of which converges on a low frequency region, are encoded to decrease the amount of information, because the signal electric power of image signals having high correlation is distributed mainly on the low frequency region. That is, the correlation of the image signals is positively utilized, so that higher compression effect is obtained in the transformation encoding method than in the estimation encoding method. However, the amount of arithmetic logic processes is larger in the transformation encoding method than in the estimation encoding method, so that the practical use of the transformation encoding method has been delayed as compared to the estimation encoding method.
In accordance with the development of computer technology, however, the calculation of orthogonal transformation required for the transformation encoding method has been easy in these days, so that the transformation encoding method has been widely used in the encoding of images. As an orthogonal transformation to a frequency region, DCT (discrete cosine transformation) is considered to be most effective for practical uses, because DCT is superior in regard to electric power converging on a low frequency region and the process speed of calculation algorithm. Among other orthogonal transformations than DCT, slant transformation, hurl transformation, etc. can be used in encoding images.
According to the conventional image compression method using DCT, however, there is a disadvantage in that an optimum compression factor is difficult to be set therein. That is, when coefficients are coarsely quantized, a data compression factor becomes large to deteriorate the quality of image. In other words, the process of the image compression is carried out with high speed, while block distortion, which is discontinuity at boundaries of blocks is generated in reproducing images. On the other hand, when the coefficients are finely quantized, the data compression factor becomes small to decrease the block distortion, while a high speed process is hindered, and the process of pictures having fast motion is difficult to be carried out.